FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2892488718> ?p ?o ?g. }

• W2892488718 endingPage "2455" @default.
• W2892488718 startingPage "2446" @default.
• W2892488718 abstract "Mass spectrometry imaging (MSI) is a tool to rapidly map the spatial location of analytes without the need for tagging or a reporter system. Niemann-Pick disease type C1 (NPC1) is a neurodegenerative, lysosomal storage disorder characterized by accumulation of unesterified cholesterol and sphingolipids in the endo-lysosomal system. Here, we use MSI to visualize lipids including cholesterol in cerebellar brain tissue from the NPC1 symptomatic mouse model and unaffected controls. To complement the imaging studies, a data-processing pipeline was developed to generate consensus mass spectra, thereby using both technical and biological image replicates to assess differences. The consensus spectra are used to determine true differences in lipid relative abundance; lipid distributions can be determined in an unbiased fashion without prior knowledge of location. We show the cerebellar distribution of gangliosides GM1, GM2, and GM3, including variants of lipid chain length. We also performed MALDI-MSI of cholesterol. Further analysis of lobules IV/V and X of the cerebellum gangliosides indicates regional differences. The specificity achieved highlights the power of MSI, and this new workflow demonstrates a universal approach for addressing reproducibility in imaging experiments applied to NPC1. Mass spectrometry imaging (MSI) is a tool to rapidly map the spatial location of analytes without the need for tagging or a reporter system. Niemann-Pick disease type C1 (NPC1) is a neurodegenerative, lysosomal storage disorder characterized by accumulation of unesterified cholesterol and sphingolipids in the endo-lysosomal system. Here, we use MSI to visualize lipids including cholesterol in cerebellar brain tissue from the NPC1 symptomatic mouse model and unaffected controls. To complement the imaging studies, a data-processing pipeline was developed to generate consensus mass spectra, thereby using both technical and biological image replicates to assess differences. The consensus spectra are used to determine true differences in lipid relative abundance; lipid distributions can be determined in an unbiased fashion without prior knowledge of location. We show the cerebellar distribution of gangliosides GM1, GM2, and GM3, including variants of lipid chain length. We also performed MALDI-MSI of cholesterol. Further analysis of lobules IV/V and X of the cerebellum gangliosides indicates regional differences. The specificity achieved highlights the power of MSI, and this new workflow demonstrates a universal approach for addressing reproducibility in imaging experiments applied to NPC1. MALDI-MS imaging (MALDI-MSI) enables label-free in situ analysis of molecules such as lipids (1.Colsch B. Jackson S.N. Dutta S. Woods A.S. Molecular microscopy of brain gangliosides: illustrating their distribution in hippocampal cell layers.ACS Chem. Neurosci. 2011; 2: 213-222Crossref PubMed Scopus (57) Google Scholar, 2.Jackson S.N. Wang H.Y. Woods A.S. In situ structural characterization of phosphatidylcholines in brain tissue using MALDI-MS/MS.J. Am. Soc. Mass Spectrom. 2005; 16: 2052-2056Crossref PubMed Scopus (156) Google Scholar, 3.Jackson S.N. Woods A.S. Direct profiling of tissue lipids by MALDI-TOFMS.J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 2009; 877: 2822-2829Crossref PubMed Scopus (60) Google Scholar), proteins (4.Stoeckli M. Chaurand P. Hallahan D.E. Caprioli R.M. Imaging mass spectrometry: a new technology for the analysis of protein expression in mammalian tissues.Nat. Med. 2001; 7: 493-496Crossref PubMed Scopus (1003) Google Scholar, 5.Chaurand P. Schwartz S.A. Billheimer D. Xu B.J. Crecelius A. Caprioli R.M. Integrating histology and imaging mass spectrometry.Anal. Chem. 2004; 76: 1145-1155Crossref PubMed Scopus (287) Google Scholar), or metabolites (6.Ly A. Buck A. Balluff B. Sun N. Gorzolka K. Feuchtinger A. Janssen K.P. Kuppen P.J. van de Velde C.J. Weirich G. et al.High-mass-resolution MALDI mass spectrometry imaging of metabolites from formalin-fixed paraffin-embedded tissue.Nat. Protoc. 2016; 11: 1428-1443Crossref PubMed Scopus (155) Google Scholar, 7.Benabdellah F. Touboul D. Brunelle A. Laprevote O. In situ primary metabolites localization on a rat brain section by chemical mass spectrometry imaging.Anal. Chem. 2009; 81: 5557-5560Crossref PubMed Scopus (75) Google Scholar) directly within tissue slices as demonstrated by Caprioli et al. (8.Caprioli R.M. Farmer T.B. Gile J. Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS.Anal. Chem. 1997; 69: 4751-4760Crossref PubMed Scopus (1676) Google Scholar). Each irradiated tissue area generates a mass spectrum from which ions of interest can be viewed relative to their location and intensity. As recently reviewed (9.Berry K.A. Hankin J.A. Barkley R.M. Spraggins J.M. Caprioli R.M. Murphy R.C. MALDI imaging of lipid biochemistry in tissues by mass spectrometry.Chem. Rev. 2011; 11: 6491-6512Crossref Scopus (263) Google Scholar), MALDI-MSI of lipids has been quite successful, given that lipids are abundant in biological tissues. Additionally, with the exception of cardiolipins and gangliosides, lipids have molecular masses between 200 and 1,000 Da, an optimal operating mass range of MALDI-TOF instruments to achieve high mass resolving power and maintain accurate mass measurements. Niemann-Pick disease type C (NPC) is a fatal, neurodegenerative, lysosomal storage disorder caused by mutations of the encoding regions of genes either for the lysosomal transmembrane protein NPC1 or the cholesterol-binding glycoprotein NPC2 (10.Patterson M.C. Vanier M.T. Suzuki K. Morris J.A. Carstea E. Neufeld E.B. Blanchette-Mackie J.E. Pentchev P. Niemann-Pick disease type C: a lipid trafficking disorder.In The Metabolic and Molecular Bases of Inherited Disease. 2001; Google Scholar), two proteins that work in tandem to mobilize cholesterol through the late endosomal/lysosomal system (11.Naureckiene S. Sleat D.E. Lackland H. Fensom A. Vanier M.T. Wattiaux R. Jadot M. Lobel P. Identification of HE1 as the second gene of Niemann-Pick C disease.Science. 2000; 290: 2298-2301Crossref PubMed Scopus (698) Google Scholar, 12.Ko D.C. Binkley J. Sidow A. Scott M.P. The integrity of a cholesterol-binding pocket in Niemann–Pick C2 protein is necessary to control lysosome cholesterol levels.Proc. Natl. Acad. Sci. USA. 2003; 100: 2518-2525Crossref PubMed Scopus (161) Google Scholar, 13.Ohgami N. Ko D.C. Thomas M. Scott M.P. Chang C.C.Y. Chang T-Y. Binding between the Niemann–Pick C1 protein and a photoactivatable cholesterol analog requires a functional sterol-sensing domain.Proc. Natl. Acad. Sci. USA. 2004; 101: 12473-12478Crossref PubMed Scopus (169) Google Scholar, 14.Infante R.E. Abi-Mosleh L. Radhakrishnan A. Dale J.D. Brown M.S. Goldstein J.L. Purified NPC1 protein. I. Binding of cholesterol and oxysterols to a 1278-amino acid membrane protein.J. Biol. Chem. 2008; 283: 1052-1063Abstract Full Text Full Text PDF PubMed Scopus (172) Google Scholar). As a result of the primary genetic defect, unesterified cholesterol and glycosphingolipids accumulate in late endosomes and lysosomes. Specifically, dysfunction of these proteins causes the inability to metabolize and traffic contents, and eventually cellular death. Cerebellar Purkinje neurons appear to be most susceptible though the cerebral cortex; thalamus and hippocampus also demonstrate neuronal loss (15.Higashi Y. Murayama S. Pentchev P.G. Suzuki K. Cerebellar degeneration in the Niemann-Pick type C mouse.Acta Neuropathol. 1993; 85: 175-184Crossref PubMed Scopus (178) Google Scholar, 16.Pentchev P.G. Brady R.O. Blanchette-Mackie E.J. Vanier M.T. Carstea E.D. Parker C.C. Goldin E. Roff C.F. The Niemann-Pick C lesion and its relationship to the intracellular distribution and utilization of LDL cholesterol.Biochim. Biophys. Acta. 1994; 1225: 235-243Crossref PubMed Scopus (107) Google Scholar, 17.Zervas M. Dobrenis K. Walkley S.U. Neurons in Niemann-Pick disease type C accumulate gangliosides as well as unesterified cholesterol and undergo dendritic and axonal alterations.J. Neuropathol. Exp. Neurol. 2001; 60: 49-64Crossref PubMed Scopus (220) Google Scholar, 18.Sun X. Marks D.L. Park W.D. Wheatley C.L. Puri V. O'Brien J.F. Kraft D.L. Lundquist P.A. Patterson M.C. Pagano R.E. et al.Niemann-Pick C variant detection by altered sphingolipid trafficking and correlation with mutations within a specific domain of NPC1.Am. J. Hum. Genet. 2001; 68: 1361-1372Abstract Full Text Full Text PDF PubMed Scopus (119) Google Scholar, 19.Sarna J.R. Larouche M. Marzban H. Sillitoe R.V. Rancourt D.E. Hawkes R. Patterned Purkinje cell degeneration in mouse models of Niemann-Pick type C disease.J. Comp. Neurol. 2003; 456: 279-291Crossref PubMed Scopus (169) Google Scholar). Systemic downstream effects include oxidative stress (20.Fu R. Yanjanin N.M. Bianconi S. Pavan W.J. Porter F.D. Oxidative stress in Niemann–Pick disease, type C.Mol. Genet. Metab. 2010; 101: 214-218Crossref PubMed Scopus (97) Google Scholar), defective calcium signaling (21.Lloyd-Evans E. Morgan A.J. He X. Smith D.A. Elliot-Smith E. Sillence D.J. Churchill G.C. Schuchman E.H. Galione A. Platt F.M. Niemann-Pick disease type C1 is a sphingosine storage disease that causes deregulation of lysosomal calcium.Nat. Med. 2008; 14: 1247-1255Crossref PubMed Scopus (622) Google Scholar), and neuroinflammation (22.Cologna S.M. Cluzeau C.V.M. Yanjanin N.M. Blank P.S. Dail M.K. Siebel S. Toth C.L. Wassif C.A. Lieberman A.P. Porter F.D. Human and mouse neuroinflammation markers in Niemann-Pick disease, type C1.J. Inherit. Metab. Dis. 2014; 37: 83-92Crossref PubMed Scopus (60) Google Scholar). The clinical phenotype of NPC is broad and includes vertical supranuclear gaze palsy, tremors, ataxia, and early dementia, and ultimately is fatal (23.Vanier M.T. Wenger D.A. Comly M.E. Rousson R. Brady R.O. Pentchev P.G. Niemann-Pick disease group C: clinical variability and diagnosis based on defective cholesterol esterification. A collaborative study on 70 patients.Clin. Genet. 2014; 33: 331-348Crossref Scopus (156) Google Scholar). While several studies have looked at transcript and protein-level alterations in NPC1 (22.Cologna S.M. Cluzeau C.V.M. Yanjanin N.M. Blank P.S. Dail M.K. Siebel S. Toth C.L. Wassif C.A. Lieberman A.P. Porter F.D. Human and mouse neuroinflammation markers in Niemann-Pick disease, type C1.J. Inherit. Metab. Dis. 2014; 37: 83-92Crossref PubMed Scopus (60) Google Scholar, 24.Nicoli E-R. Al Eisa N. Cluzeau C.V.M. Wassif C.A. Gray J. Burkert K.R. Smith D.A. Morris L. Cologna S.M. Peer C.J. et al.Defective cytochrome P450-catalysed drug metabolism in Niemann-Pick type C disease.PLoS One. 2016; 11: e0152007Crossref PubMed Scopus (16) Google Scholar, 25.Cluzeau C.V.M. Watkins-Chow D.E. Fu R. Borate B. Yanjanin N. Dail M.K. Davidson C.D. Walkley S.U. Ory D.S. Wassif C.A. et al.Microarray expression analysis and identification of serum biomarkers for Niemann–Pick disease, type C1.Hum. Mol. Genet. 2012; 21: 3632-3646Crossref PubMed Scopus (75) Google Scholar, 26.Tharkeshwar A.K. Trekker J. Vermeire W. Pauwels J. Sannerud R. Priestman D.A. te Vruchte D. Vints K. Baatsen P. Decuypere J-P. et al.A novel approach to analyze lysosomal dysfunctions through subcellular proteomics and lipidomics: the case of NPC1 deficiency.Sci. Rep. 2017; 7: 41408Crossref PubMed Scopus (71) Google Scholar, 27.Reddy J.V. Ganley I.G. Pfeffer S.R. Clues to neuro-degeneration in Niemann-Pick type C disease from global gene expression profiling.PLoS One. 2006; 1: e19Crossref PubMed Scopus (90) Google Scholar), less is known about alterations in the lipid landscape in the disease. Early work on lipid accumulation demonstrated that several tissues are affected (28.Zhou S. Davidson C. McGlynn R. Stephney G. Dobrenis K. Vanier M.T. Walkley S.U. Endosomal/lysosomal processing of gangliosides affects neuronal cholesterol sequestration in Niemann-Pick disease type C.Am. J. Pathol. 2011; 179: 890-902Abstract Full Text Full Text PDF PubMed Scopus (38) Google Scholar, 29.Kulinski A. Vance J.E. Lipid homeostasis and lipoprotein secretion in Niemann-Pick C1-deficient hepatocytes.J. Biol. Chem. 2007; 282: 1627-1637Abstract Full Text Full Text PDF PubMed Scopus (33) Google Scholar, 30.Liu Y. Wu Y-P. Wada R. Neufeld E.B. Mullin K.A. Howard A.C. Pentchev P.G. Vanier M.T. Suzuki K. Proia R.L. Alleviation of neuronal ganglioside storage does not improve the clinical course of the Niemann–Pick C disease mouse.Hum. Mol. Genet. 2000; 9: 1087-1092Crossref PubMed Scopus (84) Google Scholar). A targeted MS-based profiling study was reported in which different sphingolipids species were observed to be differential in the null NPC1 mouse model (31.Fan M. Sidhu R. Fujiwara H. Tortelli B. Zhang J. Davidson C. Walkley S.U. Bagel J.H. Vite C. Yanjanin N.M. et al.Identification of Niemann-Pick C1 disease biomarkers through sphingolipid profiling.J. Lipid Res. 2013; 54: 2800-2814Abstract Full Text Full Text PDF PubMed Scopus (80) Google Scholar) as well as in the recently generated I1061T point mutant model (32.Praggastis M. Tortelli B. Zhang J. Fujiwara H. Sidhu R. Chacko A. Chen Z. Chung C. Lieberman A.P. Sikora J. et al.A murine Niemann-Pick C1 I1061T knock-in model recapitulates the pathological features of the most prevalent human disease allele.J. Neurosci. 2015; 35: 8091-8106Crossref PubMed Scopus (72) Google Scholar). Additionally, lyso-sphingolipids in plasma and amniotic fluid have been quantified using targeted MS methods (33.Pettazzoni M. Froissart R. Pagan C. Vanier M.T. Ruet S. Latour P. Guffon N. Fouilhoux A. Germain D.P. Levade T. et al.LC-MS/MS multiplex analysis of lysosphingolipids in plasma and amniotic fluid: a novel tool for the screening of sphingolipidoses and Niemann-Pick type C disease.PLoS One. 2017; 12: e0181700Crossref PubMed Scopus (50) Google Scholar). Although whole tissue lysate lipidomics studies are invaluable, as they are sensitive, specific and can be used to obtain precise quantities, any information regarding spatial distribution is lost. In the context of lysosomal storage disorders, few studies have reported lipid imaging using MS. Lipid mapping has been performed in a mouse model of Hunter syndrome, a carbohydrate metabolism disorder in which spatial distributions of the gangliosides GM2 and GM3 were obtained alongside immunohistochemistry (34.Dufresne M. Guneysu D. Patterson N.H. Marcinkiewicz M.M. Regina A. Demeule M. Chaurand P. Multimodal detection of GM2 and GM3 lipid species in the brain of mucopolysaccharidosis type II mouse by serial imaging mass spectrometry and immunohistochemistry.Anal. Bioanal. Chem. 2017; 409: 1425-1433Crossref PubMed Scopus (38) Google Scholar). A method for enhancing neutral lipid mapping was shown in a mouse model of Fabry disease (35.Vens-Cappell S. Kouzel I.U. Kettling H. Soltwisch J. Bauwens A. Porubsky S. Muthing J. Dreisewerd K. On-tissue phospholipase C digestion for enhanced MALDI-MS imaging of neutral glycosphingolipids.Anal. Chem. 2016; 88: 5595-5599Crossref PubMed Scopus (35) Google Scholar). Other lysosomal disorders with imaging studies include Farber (36.Sikora J. Dworski S. Jones E.E. Kamani M.A. Micsenyi M.C. Sawada T. Le Faouder P. Bertrand-Michel J. Dupuy A. Dunn C.K. et al.Acid ceramidase deficiency in mice results in a broad range of central nervous system abnormalities.Am. J. Pathol. 2017; 187: 864-883Abstract Full Text Full Text PDF PubMed Scopus (32) Google Scholar), Gaucher (37.Jones E.E. Zhang W. Zhao X. Quiason C. Dale S. Shahidi-Latham S. Grabowski G.A. Setchell K.D.R. Drake R.R. Sun Y. Tissue localization of glycosphingolipid accumulation in a Gaucher disease mouse brain by LC-ESI-MS/MS and high-resolution MALDI imaging mass spectrometry.SLAS Discov. 2017; 22: 1218-1228Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar, 38.Snel M.F. Fuller M. High-spatial resolution matrix-assisted laser desorption ionization imaging analysis of glucosylceramide in spleen sections from a mouse model of Gaucher disease.Anal. Chem. 2010; 82: 3664-3670Crossref PubMed Scopus (30) Google Scholar), and Sandhoff disease (39.Marsching C. Jennemann R. Heilig R. Grone H.J. Hopf C. Sandhoff R. Quantitative imaging mass spectrometry of renal sulfatides: validation by classical mass spectrometric methods.J. Lipid Res. 2014; 55: 2343-2353Abstract Full Text Full Text PDF PubMed Scopus (25) Google Scholar, 40.Marsching C. Eckhardt M. Grone H.J. Sandhoff R. Hopf C. Imaging of complex sulfatides SM3 and SB1a in mouse kidney using MALDI-TOF/TOF mass spectrometry.Anal. Bioanal. Chem. 2011; 401: 53-64Crossref PubMed Scopus (47) Google Scholar). Recently, the I1061T NPC1 point mutant model was used to develop an infrared spectroscopy-MALDI imaging workflow. In this approach initial Fourier-transform infrared imaging data is used to guide MALDI imaging to allow for tissue annotation. The statistical component, including a t-test based feature and peak-picking extraction, was performed; however, this approach required specialized tools to obtain segmentation information (41.Rabe J-H. Sammour D.A. Schulz S. Munteanu B. Ott M. Ochs K. Hohenberger P. Marx A. Platten M. Opitz C.A. et al.Fourier transform infrared microscopy enables guidance of automated mass spectrometry imaging to predefined tissue morphologies.Sci. Rep. 2018; 8: 313Crossref PubMed Scopus (31) Google Scholar). It is also important to note that while an NPC1 model was used, this study did not look at cerebellar changes given the coronal sectioning performed nor did the authors provide insight into lipid mapping related to NPC1 disease. These reports reveal the importance of spatially localizing lipids, particularly in NPC1, which has been far more troublesome for antibody-based approaches and provide an insight into disease pathology. Given the complexity and size of MSI experiments, reproducibility is a paramount consideration in experimental design. For example, the goal of many MSI tissue profiling studies is to identify disease markers relative to their location in the sample. In order to have significance of a specific mass-to-charge ratio, any finding must be spatially, analytically, and biologically reproducible. To avoid the pursuit of “beautiful noise,” various techniques in preprocessing MSI data have been implemented (42.Norris J.L. Cornett D.S. Mobley J.A. Andersson M. Seeley E.H. Chaurand P. Caprioli R.M. Processing MALDI mass spectra to improve mass spectral direct tissue analysis.Int. J. Mass Spectrom. 2007; 260: 212-221Crossref PubMed Scopus (167) Google Scholar, 43.Tracy M.B. Chen H. Weaver D.M. Malyarenko D.I. Sasinowski M. Cazares L.H. Drake R.R. Semmes O.J. Tracy E.R. Cooke W.E. Precision enhancement of MALDI-TOF-MS using high resolution peak detection and label-free alignment.Proteomics. 2008; 8: 1530-1538Crossref PubMed Scopus (22) Google Scholar) and reviewed in greater detail (44.Ràfols P. Vilalta D. Brezmes J. Cañellas N. del Castillo E. Yanes O. Ramírez N. Correig X. Signal preprocessing, multivariate analysis and software tools for MA(LDI)-TOF mass spectrometry imaging for biological applications.Mass Spectrom. Rev. 2016; 41: 281-306Google Scholar). Pre-processing strategies apply mathematical and logical operations to raw spectral data such that replicates can be combined, compared, and analyzed ostensibly with minimized contributions from biological, instrumental, and random variance. The most common of these approaches is to normalize the total ion current to generate the image. The difficulty with such an approach is that it only averages signal variance and does not take into account the overall spectral integrity. It thereby assumes that each spectrum collected over a given area has a comparable number of features. This assumption may be acceptable when dealing with homogenous results of different chemical samples. However, imaging of biological replicates must be considered as a set of separate experiments, and thus even multiple acquisitions of serial sections can lead to great mass spectral variability. Eijkel et al. (45.Eijkel G.B. Kükrer Kaletaş B. van der Wiel I.M. Kros J.M. Luider T.M. Heeren R.M.A. Correlating MALDI and SIMS imaging mass spectrometric datasets of biological tissue surfaces.Surf. Interface Anal. 2009; 41: 675-685Crossref Scopus (55) Google Scholar) developed an algorithm to correlate secondary ion MS and MALDI imaging data from the same tissue. The authors attempted to address the data reduction of imaging experiments by conducting spectral binning to unit resolution, which is inappropriate to do when using high-resolution mass analyzers. They performed principal component analysis and canonical correlation analysis to determine unique features in their datasets, but replicate analysis was not addressed in the workflow, thus potentially leading to an underestimation of features (45.Eijkel G.B. Kükrer Kaletaş B. van der Wiel I.M. Kros J.M. Luider T.M. Heeren R.M.A. Correlating MALDI and SIMS imaging mass spectrometric datasets of biological tissue surfaces.Surf. Interface Anal. 2009; 41: 675-685Crossref Scopus (55) Google Scholar). We argue that simply publishing MSI data as representative images rather than constructs of replicate spectra underestimates the true variance between analyses, thereby potentially misleading the reader as to the significance of features. Such an approach furthermore excludes rather than incorporates the majority of data generated in the investigation. In the present study, we sought to develop an algorithm to evaluate both biological and technical replicate imaging experiments and then identify altered lipids and map their spatial distribution using a mouse model of NPC1. We imaged the cerebellum of 7-week-old null BALB/c-Npcnih, hereafter Npc1−/− (46.Pentchev P.G. Comly M.E. Kruth H.S. Patel S. Proestel M. Weintroub H. The cholesterol storage disorder of the mutant BALB/c mouse. A primary genetic lesion closely linked to defective esterification of exogenously derived cholesterol and its relationship to human type C Niemann-Pick disease.J. Biol. Chem. 1986; 261: 2772-2777Abstract Full Text PDF PubMed Google Scholar), and control littermates, using MALDI-MSI. Relative to the disease progression, the 7-week time point displays classical phenotypes of ataxia and tremors that recapitulate the human disease. The newly developed algorithm was used to evaluate Npc1+/+ and Npc1−/− MSI spectra datasets of the cerebellum to validate reproducibility between replicates. This method provides an unbiased process to screen for unique and biologically interesting features that would not be detected from a single tissue image alone and also provides a way to form representative mass spectra for a dataset of replicates. All reagents were used as supplied unless otherwise noted. Purified water was obtained via a Barnstead GenPure (Thermo Fisher Scientific). All reagents were obtained from Sigma-Aldrich unless noted. Hematoxylin was purchased from Ricca Chemical Co. All experiments were performed in accordance with University of Illinois at Chicago IACUC-approved protocols. Balb/c npcnih (Npc1+/−) mice were obtained from Jackson Laboratories (RRID:IMSR JAX:003092), and a breeding colony was maintained in our laboratory. Genotyping was performed using polymerase chain reaction as previously reported (17.Zervas M. Dobrenis K. Walkley S.U. Neurons in Niemann-Pick disease type C accumulate gangliosides as well as unesterified cholesterol and undergo dendritic and axonal alterations.J. Neuropathol. Exp. Neurol. 2001; 60: 49-64Crossref PubMed Scopus (220) Google Scholar). The primer sequences used for genotyping were: (FWD8F) 5′-GGTGCTGGACAGCCAAGTA-3′ and (REVINTR3) 5′-GATGGTCTGTTCTCCCATG-3′. At 7 weeks of age, control (Npc1+/+) and null mutant (Npc1−/−) mice were euthanized via CO2 asphyxiation followed by decapitation. Whole brain tissue was dissected and immediately frozen in dry ice to maintain spatial integrity and stored at −80°C. Tissue staining was performed using rehydration and dehydration steps. Briefly, tissue sections on microscope slides were immersed in 95% ethanol solution for 30 s, 70% ethanol solution for 30 s, purified deionized water for 30 s, hematoxylin solution for 30 s, 100 mM ammonium carbonate solution for 20 s, 70% ethanol solution for 30 s, 95% ethanol solution for 30 s, 30 s in eosin solutions, 30 s in 100% ethanol, and then 2.5 min in xylene. The stained tissue was viewed using an Evos XL Core (Life Technologies) and to obtain the final image. Frozen, intact brain was cryosectioned at −20°C using a Microm HM 525 (Thermo Fisher Scientific). Serial tissue sections of 16 μm thickness were thaw-mounted directly on MALDI stainless steel target plates and optical microscope slides for H&E staining and then were placed under vacuum for 10 min, then stored at −80°C until further analysis. The MALDI stainless-steel plate was dried under vacuum for 10 min to remove residual moisture. The plate containing the tissue section was then submerged in 50 mM ammonium formate solution (Alfa Aesar) for 20 s (47.Angel P.M. Spraggins J.M. Baldwin H.S. Caprioli R. Enhanced sensitivity for high spatial resolution lipid analysis by negative ion mode matrix assisted laser desorption ionization imaging mass spectrometry.Anal. Chem. 2012; 84: 1557-1564Crossref PubMed Scopus (160) Google Scholar). Matrix application was conducted using an artist-model airbrush to produce an even coating. The matrix 9-aminoacridine was prepared at 10 mg/ml concentration in acetone (Thermo Fisher Scientific). In an effort to have reproducible matrix application, the density of matrix applied was calculated by weighing the target plates before and after the application with the desired amount of matrix being 0.15–0.25 mg/cm2. The analysis of matrix deposition is provided in supplemental Fig. S1. The mass spectrum for the on-tissue analysis (supplemental Fig. S1A–D) is provided for each replicate to evaluate m/z 612.3, a matrix ion of 1,5-diamino­napthalene (48.Kaya I. Michno W. Brinet D. Iacone Y. Zanni G. Blennow K. Zetterberg H. Hanrieder J. Histology-compatible MALDI mass spectrometry based imaging of neuronal lipids for subsequent immunofluorescent staining.Anal. Chem. 2017; 89: 4685-4694Crossref PubMed Scopus (43) Google Scholar). An example image of a matrix ion is provided to demonstrate reproducible matrix application (supplemental Fig. S1E). Slight differences are observed from the tissue compared with the stainless-steel plate, which is confirmed by recent reports of ion suppression in MALDI-MSI experiments (49.Taylor A.J. Dexter A. Bunch J. Exploring ion suppression in mass spectrometry imaging of a heterogeneous tissue.Anal. Chem. 2018; 90: 5637-5645Crossref PubMed Scopus (77) Google Scholar). Biological replicate analyses (n = 5 Npc1+/+, n = 6 Npc1−/−) were conducted with n = 3–4 technical replicates (serial sections) collected for each animal. Matrix sublimation of dihydroxybenzoic acid (DHB; Sigma-Aldrich) was conducted for cholesterol imaging using a homemade sublimation apparatus. DHB matrix was dissolved in acetone (30 mg/ml) and transferred into the bottom of the sublimation apparatus, then evaporated using a stream of nitrogen gas. The preweighed target plate was then attached to the flat bottom of the apparatus using copper tape. The sand bath temperature was set to 120°C, and the trap was filled with ice slush. The internal vacuum was kept at 80 mTorr before starting the sublimation which lasts for 2 min. The target plate was weighed again and measured to obtain the density. Initial lipid assignments were made by comparing accurate mass measurements with the LIPID MAPS database (http://www.lipidmaps.org). Second, tandem MS data was acquired to yield signature fragment ions of each lipid species. MSI was performed using a model 4800 Plus MALDI TOF/TOF Analyzer (Sciex) equipped with a 200 Hz Nd-YAG pulsed laser (355 nm). The approximate laser spot size was 90 µm. Data were acquired in both the positive and negative ion reflectron modes as separate experiments. Red phosphorus was used for external mass calibration as previously described (50.Sládková K. Houska J. Havel J. Laser desorption ionization of red phosphorus clusters and their use for mass calibration in time-of-flight mass spectrometry.Rapid Commun. Mass Spectrom. 2009; 23: 3114-3118Crossref PubMed Scopus (82) Google Scholar). The number of laser shots per pixel was set at 255 and the raster distance between each pixel was set to 50 μm using the 4800 Imaging Tool (version 3.2;, M. Stoeckli). Data processing for the MS ion images was conducted using TissueView software (Version 1.1; Sciex) or MSiReader (51.Robichaud G. Garrard K.P. Barry J.A. Muddiman D.C. MSiReader: an open-source interface to view and analyze high resolving power MS imaging files on Matlab platform.J. Am. Soc. Mass Spectrom. 2013; 24: 718-721Crossref PubMed Scopus (276) Google Scholar). Regions-of-interest were determined based on ion intensities compared with the MALDI plate which was then compared with a representative H&E-stained section. Data analysis was carried out using the R-Programming Language (https://www.r-project.org/about.html). Cerebellar tissue from three Npc1+/+ and Npc1−/− animals at 7 weeks of age were homogenized in 1X PBS. Protein concentration was measured using the Pierce BCA Protein Assay (Thermo Scientific). Extraction of cerebellar lipids from aliquots of each homogenized tissue was carried out using a modified chloroform/methanol method to extract gangliosides originally developed by Folch et. al (52.Folch J. Lees M. Sloane Stanley G. A simple method for the isolation and purification of total lipids from animal tissues.J. Biol. Chem. 1957; 226: 497-509Abstract Full Text PDF PubMed Google Scholar). The upper aqueous layer from the chloroform/methanol protocol was collected, and the lipi" @default.
• W2892488718 created "2018-10-05" @default.
• W2892488718 creator A5006294096 @default.
• W2892488718 creator A5077073094 @default.
• W2892488718 creator A5082245282 @default.
• W2892488718 date "2018-12-01" @default.
• W2892488718 modified "2023-09-24" @default.
• W2892488718 title "Mass spectrometry imaging of lipids: untargeted consensus spectra reveal spatial distributions in Niemann-Pick disease type C1" @default.
• W2892488718 cites W1481650860 @default.
• W2892488718 cites W1599833391 @default.
• W2892488718 cites W1623462303 @default.
• W2892488718 cites W1976208596 @default.
• W2892488718 cites W1976704599 @default.
• W2892488718 cites W1982216518 @default.
• W2892488718 cites W1982479470 @default.
• W2892488718 cites W2000915110 @default.
• W2892488718 cites W2002363184 @default.
• W2892488718 cites W2004893995 @default.
• W2892488718 cites W2005256936 @default.
• W2892488718 cites W2005740166 @default.
• W2892488718 cites W2018809823 @default.
• W2892488718 cites W2024523213 @default.
• W2892488718 cites W2033278243 @default.
• W2892488718 cites W2040407461 @default.
• W2892488718 cites W2043929943 @default.
• W2892488718 cites W2044272444 @default.
• W2892488718 cites W2045083711 @default.
• W2892488718 cites W2048269418 @default.
• W2892488718 cites W2049092217 @default.
• W2892488718 cites W2052510647 @default.
• W2892488718 cites W2053203314 @default.
• W2892488718 cites W2060429862 @default.
• W2892488718 cites W2060761584 @default.
• W2892488718 cites W2061637917 @default.
• W2892488718 cites W2064978465 @default.
• W2892488718 cites W2067389447 @default.
• W2892488718 cites W2075247874 @default.
• W2892488718 cites W2078485691 @default.
• W2892488718 cites W2083957918 @default.
• W2892488718 cites W2086298571 @default.
• W2892488718 cites W2093996758 @default.
• W2892488718 cites W2098602667 @default.
• W2892488718 cites W2109376993 @default.
• W2892488718 cites W2119814716 @default.
• W2892488718 cites W2129032292 @default.
• W2892488718 cites W2138786573 @default.
• W2892488718 cites W2143142801 @default.
• W2892488718 cites W2147502416 @default.
• W2892488718 cites W2160059259 @default.
• W2892488718 cites W2166539605 @default.
• W2892488718 cites W2168526937 @default.
• W2892488718 cites W2307447599 @default.
• W2892488718 cites W2325927456 @default.
• W2892488718 cites W2335525544 @default.
• W2892488718 cites W2367049629 @default.
• W2892488718 cites W2400221597 @default.
• W2892488718 cites W2463662776 @default.
• W2892488718 cites W2554565295 @default.
• W2892488718 cites W2581510101 @default.
• W2892488718 cites W2600880639 @default.
• W2892488718 cites W2603429207 @default.
• W2892488718 cites W2604417788 @default.
• W2892488718 cites W2738624927 @default.
• W2892488718 cites W2741419829 @default.
• W2892488718 cites W2781990131 @default.
• W2892488718 cites W2787901270 @default.
• W2892488718 cites W287983420 @default.
• W2892488718 doi "https://doi.org/10.1194/jlr.d086090" @default.
• W2892488718 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6277165" @default.
• W2892488718 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30266834" @default.
• W2892488718 hasPublicationYear "2018" @default.
• W2892488718 type Work @default.
• W2892488718 sameAs 2892488718 @default.
• W2892488718 citedByCount "21" @default.
• W2892488718 countsByYear W28924887182019 @default.
• W2892488718 countsByYear W28924887182020 @default.
• W2892488718 countsByYear W28924887182021 @default.
• W2892488718 countsByYear W28924887182023 @default.
• W2892488718 crossrefType "journal-article" @default.
• W2892488718 hasAuthorship W2892488718A5006294096 @default.
• W2892488718 hasAuthorship W2892488718A5077073094 @default.
• W2892488718 hasAuthorship W2892488718A5082245282 @default.
• W2892488718 hasBestOaLocation W28924887181 @default.
• W2892488718 hasConcept C162356407 @default.
• W2892488718 hasConcept C185592680 @default.
• W2892488718 hasConcept C24066741 @default.
• W2892488718 hasConcept C43617362 @default.
• W2892488718 hasConceptScore W2892488718C162356407 @default.
• W2892488718 hasConceptScore W2892488718C185592680 @default.
• W2892488718 hasConceptScore W2892488718C24066741 @default.
• W2892488718 hasConceptScore W2892488718C43617362 @default.
• W2892488718 hasFunder F4320306794 @default.
• W2892488718 hasFunder F4320332697 @default.
• W2892488718 hasIssue "12" @default.
• W2892488718 hasLocation W28924887181 @default.
• W2892488718 hasLocation W28924887182 @default.
• W2892488718 hasLocation W28924887183 @default.
• W2892488718 hasOpenAccess W2892488718 @default.

• next